Numerical analysis of feedforward concepts for advanced control of organic Rankine cycle systems on heavy-duty vehicles

Abstract

Organic Rankine cycle systems are the most promising technology to recover the waste heat from heavy-duty vehicles in an efficient and economical way, thus increasing their energy efficiency and reducing their environmental impact. A major challenge for an efficient and profitable integration of the organic Rankine cycle unit is presented by the highly transient nature of the waste heat during a driving cycle. In order to cope with the rapid fluctuations of the waste heat and to ensure safe operation, advanced control techniques have gained particular attention in the last decade. This paper presents novel high-order advanced feedforward control concepts for organic Rankine cycle units that improve the performance of classical proportional integral controllers. The proposed approach enables the use of high-order nonlinear models for feedforward control of organic Rankine cycle systems, therefore allowing for more accurate estimation of the desired control action. As a reference, a proportional integral controller with feedforward is presented, acting on the pump mass flow rate to control the degree of superheating at the turbine inlet, which is a key variable to ensure high power output and safe operation of the organic Rankine cycle system. Static, linear and nonlinear dynamic inversed-model feedforward controllers were integrated with a classical proportional integral controller and numerically evaluated under a realistic waste heat profile of a heavy-duty truck. The results suggest that the static and the linear feedforward concepts do not offer any advantages compared with the classical proportional integral controller, because they result in a higher absolute mean square tracking error and a higher cumulative controller effort. Instead, the high-order nonlinear dynamic inversed-model feedforward controller introduced in this work offers important advantages compared with the classical proportional integral controller by reducing the absolute root mean square tracking error from 10.8 K to 2.2 K without excessively increasing the controller cumulative effort (limited to 1.9%/s). On the contrary, the classical proportional integral controller could optimize only one of the objectives at the expenses of the other. The proposed control approach significantly improves the operation of the organic Rankine cycle unit, limiting the fluctuations of the degree of superheating and keeping this quantity within ±7 K of the desired set point. Thus, the novel feedforward concept will be highly beneficial in integrating classical proportional integral control of organic Rankine cycle units that involve highly transient heat sources.